Your partner in service-driven supply chain planning and optimization
Align demand, supply, inventory and service levels across complex supply chains
About Us
We specialize in AI-enabled Probabilistic Solutions for supply chain planning. This is is not another S&OP solution, instead the primary focus is on achieving exceptional service levels, inventory accuracy and optimizing working capital.
Most other S&OP tools use deterministic methods and operate at monthly aggregate levels. They often rely on Time Series-based forecasting, ABC inventory segmentation, and MRP-style, single-echelon replenishment planning. These approaches, which consolidate data into monthly buckets, can obscure critical signals at granular, line-order levels, leading to inaccurate planning and a disconnect from daily execution.
By shifting to Probabilistic models and service-driven planning, customers achieve more accurate, actionable plans that translate seamlessly into daily operations. This results in optimized inventory levels and superior service performance across the supply chain.
Probabilistic demand modeling and forecasting
ToolsGroup’s probabilistic demand planning software provides a range of possible outcomes along with their probabilities. Our demand modeling lets you layer demand sensing insights atop the statistical forecast, creating a demand plan that optimizes each SKU against target service levels. This ensures reliable operations planning and sales forecasting for your demand management and operational planning needs.
Demand models are inherently stochastic, capturing demand variability and order-line frequencies as probabilistic distribution functions. Our proprietary Frequency Based Forecasting technology automatically understands key demand characteristics, enabling reactive adjustments to unexpected signals and enhancing your ability to respond to changes in demand.
Demand Planning
Probabilistic demand models seamlessly integrates both bottom-up and top-down planning. Our demand planning tool gives you an accurate forecast for inventory optimization, and a planning process you can trust. Enjoy the freedom to focus on the areas of inventory management that matter the most, using analytics to identify demand drivers, understand the impact of seasonality, and improve your overall inventory management.
Service Optimizer software meticulously model various demand signals and demand drivers, encompassing baseline forecasts, trends, patterns, seasonality, new product introductions, product replacements, promotions, special actions, and market intelligence etc. Through this approach, your planners can construct a comprehensive statistical demand profile that incorporates contributions from each of these distinct demand drivers. Each driver's contribution will be meticulously modeled at the most granular level and dynamically adjusted over time, enhancing organization's ability to sense demand fluctuations accurately. This methodology empowers supply chains to capture and respond to changes in demand signals with greater precision.
Demand Sensing
Demand sensing improves service and minimizes inventory. Supply Chains can react faster to market changes. Demand sensing has enabled ToolsGroup clients to improve forecast accuracy by 15-40%, decrease inventory by 10-30%, and improve customer service levels by two to five percentage points.
Demand Sensing reduce downstream demand latency. Extract relevant information directly from PoS data to improve your sales forecast without waiting for your distributors or retailers. Getting earlier demand insights enables you to create more accurate short-term plans and reduce expediting.
Demand Collaboration
Demand Collaboration Hub combines demand and forecast data from multiple sources. The user-friendly environment empowers even inexperienced or casual users from inside or outside your organization to easily collaborate and participate in the demand planning and forecasting process. This can incorporate calendarized workflows and signoffs among various demand stakeholders in the demand collaboration hierarchy.
Inventory Optimization
Automate Inventory and Service Level Planning, delivering insights on what, where, when, and how much to carry. Our Multi-Echelon Inventory Planning (MEIO) optimize inventory along mix, stage, and lot size, while dynamically adjusting to changing demand patterns and supply side status vectors.
When managing slow-moving and intermittent demand items, ToolsGroup is incomparably better. Our proprietary probabilistic algorithms can model stock-to-service relationships reliably, even for very slow moving and intermittent demand items. This allows the system to optimize even very large assortments, including products in the “long tail”, balancing inventories across different locations in the distribution network and all the way up to different levels in the bill of materials (BOM).
ToolsGroup's proprietary Stock-to-Service Inventory models allow for strategic business decisions by facilitating interaction between Sales, Supply Chain, and Finance teams, who can agree on business policies based on stock-to-service scenarios. The strategies agreed upon can be directly applied to the model, which then translates this high-level policy decisions into detailed Service Levels and Safety Stocks for each item and at each location. This approach enables to maintain optimal inventory levels while meeting outstanding service level targets and commitments.
Dynamic Replenishment
Multi-echelon Replenishment Planning process Stochastic Demand Signals Across the Network and to the Bills of Material, against changing status vectors. This create dynamic proposals to ensure material movements across the network – down to the Dealer or Store level – to achieve service targets.
Time-phased Replenishment Demand is updated on a daily, rolling basis in response to changing variables like promotions, seasonality and supply constraints. Time-phased Min and Max net requirements that incorporate the statistical demand and supply characteristics; automatically creates constrained replenishment and transfer proposals to balance the network.
Multi-echelon replenishment planning have production and procurement planning tightly integrated with Distribution Planning so that Bullwhip can be tackled all the way upstream, to production and procurement.
Machine Learning
Self-learning, self-calibrating application. Demand, Inventory and Supply models are automatically generated from raw data, both structured and unstructured, and on continuous, ongoing basis. SO99+ includes unique machine learning technology able to glean market learning from Big Data and apply to the forecast (NPI, Promotion Planning, and Causal Factors). This is a unique offering
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